Genetic diversity is very important in crop improvement. This study was carried out to assess the genetic diversity and the number of unique multilocus genotypes (MLGs) in a cassava collection in Burkina Faso. To achieve this objective, 130 cassava accessions were genotyped using 32 simple sequence repeat (SSR) markers. The results revealed that among these markers, twelve (12) were highly informative, with polymorphic information content (PIC) values greater than 0.50; twelve (12) were moderately informative, with PIC values ranging between 0.25 and 0.50; and eight (8) were not very informative, with PIC values lower than 0.25. A moderate level of genetic diversity was found for the population, indicated by the average expected heterozygosity (0.45) and the observed heterozygosity (0.48). About 83.8% of unique multilocus genotypes were found in the cassava collection, indicating that SSR markers seem to be most appropriate for MLG identification. Population structure analysis based on hierarchical clustering identified two subpopulations and the Bayesian approach suggested five clusters. Additionally, discriminant analysis of principal components (DAPC) separated the cassava accessions into 13 subpopulations. A comparison of these results and those of a previous study using single nucleotide polymorphisms (SNP) suggests that each type of marker can be used to assess the genetic structure of cassava grown in Burkina Faso.

Cassava adaptation to climate change and its resistance to diseases are essential prerequisites for achieving food security in sub-Saharan Africa. The accessions collected from farmers’ fields are very important because they can provide new sources of genetic variability that are essential to achieve this goal. In this study, a panel of 184 accessions collected in Burkina Faso was genotyped using 36 single nucleotide polymorphism (SNP) markers. The accessions and markers that presented with more than 6% missing data were removed from the dataset and the remaining 34 markers and 166 accessions were retained for genetic diversity and population structure assessment. The average values of expected heterozygosity (0.46), observed heterozygosity (0.58), and polymorphic information content (0.36) indicated high genetic diversity within accessions. A complex genetic structure of 166 accessions was observed through the formation of 17 clusters using discriminant analysis of principal components (DAPC) and two clusters using Bayesian analysis. Out of the 166 accessions, 79 were unique multilocus genotypes (MLGs) and 87 were potentially duplicates. From the 79 MLGs, DAPC suggested eight clusters while the Bayesian analysis suggested seven clusters. Clusters shaped by DAPC appeared to be more consistent with a higher probability of assignment of the accessions within the clusters. Principal Coordinate Analysis (PCoA) showed a lack of clustering according to geographical origin. Information related to breeding patterns and geographic origin did not allow for a clear differentiation between the clusters according to the analysis of molecular variance (AMOVA). The results of this study will be useful for cassava germplasm conservation and breeding programs.

Genetic diversity is very important in crop improvement. This study was carried out to assess the genetic diversity and the number of unique multilocus genotypes (MLGs) in cassava collection in Burkina Faso. To achieve this objective 130 cassava accessions were genotyped using 32 simple sequence repeat (SSR) markers. The results revealed that among these markers, twelve (12) were highly informative, with the PIC values greater than 0.50, twelve (12) were moderately informative, with the PIC values ranged between 0.25 and 0.50, and eight (8) were not very informative, with the PIC values lower than 0.25. A moderate level of genetic diversity was found for the population, indicated by the average expected heterozygosity (0.45) and the observed heterozygosity (0.48). About 83.8% of unique multilocus genotypes were found in the cassava collection indicating that SSR markers seem to be most appropriate for MLGs identification. Population structure analysis based on hierarchical clustering identified two subpopulations and Bayesian approach suggested five clusters. Additionally, DAPC analysis separated the cassava accessions into 13 subpopulations. The comparison of these results and the previous study using SNP, suggest that each type of markers can be used to assessment the genetic structure of cassava grown in Burkina Faso.